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Exclusive to Arthur, we're partnering with an innovative, technology-led UK insurer that has built its reputation by solving some of the most complex challenges in home insurance. Operating at the intersection of data science, geospatial intelligence and underwriting, the business has spent over two decades using technology and analytics to better understand risk and provide cover where others cannot. As they continue to invest in advanced pricing capabilities, they are looking to appoint an R&D Manager – Risk Pricing & Geospatial Analytics to lead the discovery, development and deployment of next-generation risk signals that drive underwriting and pricing performance. This is a rare opportunity for a senior analyst, principal analyst or technical lead to step into a highly visible leadership role where you'll influence strategy, build new capabilities and see your work deployed directly into production.
Job Responsibility
Lead the discovery, testing and deployment of new geospatial and peril-based pricing variables
Build and execute a third-party data strategy, identifying and integrating external datasets that improve risk selection and pricing accuracy
Develop innovative address-level risk features using geospatial, property and environmental data
Build, validate and benchmark predictive models across frequency, severity and large-loss propensity
Evaluate new data vendors, run proof-of-concepts and quantify commercial value
Translate R&D concepts into production-ready pricing features and models
Integrate hazard, exposure and vulnerability data to improve understanding of complex property risks
Support model governance, monitoring, explainability and regulatory compliance
Hire and grow the team in 2027
Present recommendations to senior stakeholders and influence strategic decision-making
Requirements
Extensive experience within insurance pricing, data science, catastrophe modelling, geospatial analytics or related risk functions
Strong household insurance experience
A track record of delivering predictive models, pricing features or data products into production environments
Experience working with third-party geospatial, environmental or property datasets
Strong technical capability across Python, R and SQL
Experience using GIS technologies such as QGIS, ArcGIS, GeoPandas or PostGIS
Understanding of model governance, explainability and regulatory requirements
Excellent stakeholder management and communication skills